The present invention relates to apparatus for processing documents arising in financial transactions which include numerical figures, such as bank checks, credit card drafts, and the like. More specifically, the invention relates to apparatus for automatically locating and reading handwritten numeric entries on the documents and balancing and/or reconciling the underlying transaction.
The standard format for bank checks includes a first location in which the dollar amount of the check is spelled out in alphabetic characters and a second location in which the dollar amount is entered in numerical figures. The numeric dollar amount is known as the courtesy amount, and the location on the check in which this amount is written is known as the courtesy amount field. By comparison, the alphabetic amount entry is known as the legal amount.
To assist the bank in processing deposits, at the time of making a deposit the depositor fills out a slip, on which are entered the total deposit amount and dollar amounts of the cash and individual checks making up the deposit. For an individual account, the deposit will generally include only a relatively few checks. For a merchant account, the deposit may include the merchant's receipts for a full day or longer period. In either event, the deposit is accompanied by a deposit slip (sometimes referred to as a deposit ticket or merchant draft for commercial accounts), on which the total deposit amount is indicated.
When the bank later processes the deposit, the dollar amounts of the individual checks and cash making up the deposit are entered into a computer data base along with other relevant data from the check or deposit slip. As a verification that the dollar amounts have been correctly entered, the deposit is subjected to a balancing operation, in which, among other things, the sum of the individual checks is compared with the total on the deposit slip (less any cash deposit). If the total deposit as computed from the individual check amounts entered into the data base does not agree with the total entered from the deposit slip, then the batch is subjected to a separate reconciliation operation to find the error. This operation frequently involves visual inspection of each individual check until the error is found. A large bank may process as many as several hundred thousand checks per day. Given the large volume of checks to be processed, the dollar-amount entry, balancing, and reconciliation procedures are labor-intensive, slow, and costly.
Various automatic apparatus has been developed to reduce the labor and increase the speed with which checks can be processed. Much of the data appearing on checks and deposit slips, for example, is printed in machine-readable form. The payor bank and payor account number normally will be printed on the individual checks in a type font suitable for optical character recognition (OCR) or with magnetic ink for magnetic ink character recognition (MICR). The depositor's account number will similarly appear on the deposit slip in OCR and/or MICR characters.
The use of OCR and MICR encoded characters greatly facilitates processing because these characters may rapidly and automatically be scanned, recognized, and entered into the data base with high reliability. Handwritten dollar amounts on checks and deposit slips, however, are not so amenable to these techniques due to the unconstrained nature of handwritten characters and the great variety of handwriting styles.
The problem of automatically reading handwritten alphanumeric characters has been addressed by a number of authors. See, for example, "Automatic Recognition of Print and Script," by L. D. Harmon, Proceedings of the IEEE, (October 1972), which provides a general review, and the following publications, which discuss specific approaches: "Recognition of Handprinted Characters for Automated Cartography," by M. Lybanon and L. K. Gronmeyer, SPIE, Vol. 155, p. 56, Image Understanding Systems & Industrial Applications (1979); "Recognition of Handprinted Characters by an Outermost Point Method," by K. Yamamoto and S. Mori, Pattern Recognition, Vol. 12, p. 189 (Pergamon Press Ltd., 1980); "A Combination of Statistical and Syntactical Pattern Recognition Applied to Classification of Unconstrained Handwritten Numerals," by B. Duerr, W. Haettich, H. Tropf and G. Winkler, Pattern Recognition, Vol. 12, p. 189 (Pergamon Press Ltd., 1980).
Despite the efforts to develop improved methods for reading handwritten characters, known automatic recognition techniques are still prone to errors. Recognition errors may be of two types. One type, referred to as confusion error, occurs when a character cannot be recognized at all. The other type, referred to as substitution error, occurs when a character is misread and identified as the wrong character. Confusion errors are easily signaled by the recognition apparatus and may be corrected by a human operator, who keys the correct amount by hand from the check or deposit slip itself. Substitution errors, on the other hand, are more difficult to detect and threaten the integrity of the financial transaction data records. The cost in time and labor to find and correct a substitution error may far outweigh the value of the underlying transaction. Automatic recognition of handwritten dollar amounts on checks and other bank documents has generally not been embraced by the banking industry because it has not been found to reduce the labor involved in processing checks and, in fact, it may even increase labor requirements because of the extra effort needed for handling the error stream generated.
A system greatly reducing the amount of labor needed to process financial documents such as checks is disclosed in U.S. Pat. No. 4,205,780. In that system, the checks or other documents are processed almost entirely electronically. The images of all the checks in a batch along with the deposit slip (and typically along with numerous other batches) are captured electronically from a rapidly moving transport and stored for subsequent processing. After capture and storage, the documents and transactions are processed electronically with minimal need to handle the paper checks or other documents. In this system, it is still necessary for human operators for to read and key the dollar amounts from the individual checks and deposit slips. Here, however, the operators read the dollar amount from the image displayed at a video terminal. Verification that the correct dollar amounts have been entered may be performed, in the first instance, by having two separate key operators enter the dollar amount for each check. If the two entries do not agree, then the system calls for a correction. The system then proceeds to balancing by comparing the total of the individual checks with the total amount keyed from the deposit slip. Any discrepancy here goes to a reconciliation procedure, which is again performed from the video terminals. This system greatly speeds up the processing of checks, among other reasons, because the dollar amounts may be keyed from the images displayed at the video terminals much faster than from the paper checks themselves, and any discrepancies may quickly be discovered and corrected at the video terminals. Furthermore, the system greatly reduces the labor demand because it is not necessary to physically handle each check and physically carry the batches of checks from station to station.
Machine recognition of handwritten dollar amounts has proved difficult primarily for two reasons. First, the precise position on the check where the courtesy amount is written is not standard, but exhibits a range of variation depending on the style of the check. Second, the great variation in handwriting styles multiplies the complexity of the recognition problem, with the result that known attempts at automatically reading the courtesy amount have not been able to do so sufficiently reliably to be acceptable in banking and other financial institutions.